Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms-Reference-Cited by-同舟云学术

Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms

Published:2011-06 Issue:6 Volume:14 Page:521-525
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Ozsert M.,Yavuz O.,Durak-Ata L.

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

http://www.tandfonline.com/doi/pdf/10.1080/10255842.2010.485130

Reference17 articles.

1. A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait

2. A Real-Time EMG Pattern Recognition System Based on Linear-Nonlinear Feature Projection for a Multifunction Myoelectric Hand

3. A Supervised Feature-Projection-Based Real-Time EMG Pattern Recognition for Multifunction Myoelectric Hand Control

4. Upper Extremity Limb Function Discrimination Using EMG Signal Analysis

5. Fang J, Agarwal GC, Shahani BT. 1997. Decomposition of EMG signals by wavelet spectrum matching. Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. p. 1253–1256

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